QRadCom: Quantum-Assisted Source and Symbol Detection Framework in a Radar Communication System With Low-Computational Complexity

Radar communication system (RadCom) is an emerging area in vehicular technology that provides efficient bandwidth allocation for joint detection of communication symbols and source detection in radar. This finds application in vehicle-to-anything (V2X) system. Towards next-generation communication, such intelligent system requires both accuracy and complexity efficient algorithms for reliable use cases. Classical super-resolution algorithms that provide the high accuracy in parameter estimation are built on matrix sub-space method incurring high computational complexity. By achieving a performance nearly as accurate as that of the classical RadCom algorithm for target detection in radar and mean square error (MSE) performances in communication system, we introduce a quantum-assisted signal processing for radar communication, known as QRadCom. The key contribution in this work is the significant computational complexity reduction with the proposed quantum formalism-based QRadCom, compared to its classical counterpart. Considering a multi-tap communication channel, we demonstrate a quantum-assisted symbol detection and source identification algorithm for a single-input and multiple-output (SIMO) antenna configuration. Further, using random matrix theory for the large-dimensional channel matrix, we derive an approximate bound for the mean square error in the QRadCom system. Numerical results manifest the efficacy of the proposed QRadCom in terms of computational complexity improvement and nearly same performance compared to the classical algorithm.